Analytics Engineer — Build Trusted Data Models at Scale

Relevance Ventures; New York (NY); On-site; USD 110,000 - 140,000; Full time

Job summary

Talkiatry is seeking an Analytics Engineer to join a team building a governed data foundation that powers decision-making. You will design and maintain reliable, well-documented data models using dbt, Snowflake, and Databricks to serve as the trusted data backbone for stakeholders.

You will collaborate with engineers and stakeholders to translate business questions into reusable data products, support a self-service analytics environment, and help evolve governance and data quality standards

Qualifications

• 2–3 years in analytics engineering or data engineering
• Proficient SQL with data modeling concepts
• Hands-on with dbt and cloud data warehouses (Snowflake/BigQuery)
• Familiarity with BI tools such as Omni, Looker, or Tableau
• Bias toward reusable, governed data products and cross-functional collaboration
• Clear communication of data concepts to varied audiences

Responsibilities

• Build and maintain clean, scalable data models using dbt, Snowflake, and Databricks
• Translate business questions into governed data products, not one-off reports
• Contribute to a self-service analytics environment with reliable models
• Uphold data governance, data quality, and documentation standards
• Support dashboards and reporting with a focus on enabling stakeholders
• Collaborate with data and engineering teams to integrate data products into development processes

Skills

Analytics Eng exp

SQL proficiency

Data modeling

dbt experience

BI tools knowledge

Stakeholder comms

Tools

dbt

Snowflake

BigQuery

Looker

Tableau

Omni

Job description

Talkiatry is seeking an Analytics Engineer to join a team building a governed data foundation that powers decision-making. You will design and maintain reliable, well-documented data models using dbt, Snowflake, and Databricks to serve as the trusted data backbone for stakeholders.

You will collaborate with engineers and stakeholders to translate business questions into reusable data products, support a self-service analytics environment, and help evolve governance and data quality standards